The current rise in skin cancer incidence and the increased public awareness of the dangers of skin cancer has reinforced a need for tracking of skin lesions in a reliable and accurate fashion. Most important is the need for a method of early detection of melanoma, the deadliest skin cancer. Until recently, when a physician noted a lesion on a patient the method of recording was through painstaking notes and measurements. However, this is not necessarily an objective nor sufficiently stringent method of follow-up and may be insufficient for accurate diagnosis.
In order to standardize the notetaking procedure, the clinical ABCD system for checking static clinical features was introduced by the NYU Medical Center. In this system a lesion is checked for Asymmetry, Border irregularity, Color variegation and Diameter. Diagnosis based on the clinical ABCD system has achieved a sensitivity of roughly 80%. This low sensitivity has led to the practice of removing almost any atypical mole. In addition, the ABCD system can only be applied to moles greater than 6 mm in diameter. It would be desirable to detect malignant moles at an even earlier stage.
In Great Britain, the Seven Point Checklist was introduced to improve the sensitivity of the clinical exam. In this method, three major features (change in size, shape or color) and four minor features (inflammation, crusting or bleeding, sensory change and diameter greater than 7 mm) are assessed. The inclusion of both static and dynamic change has led to a higher sensitivity in diagnosis. The emphasis on change in this method shows the dynamics of the lesion. However, the system has not gained wide acceptance because there have not been enough studies in order to quantify what rate of changes are considered alarming, since there are various rates of change which are acceptable and these rates may vary according to the individual. In addition, applications of this system have led to low specificity. Some of the parameters of the checklist are subjective, such as the sensory ones, and hence may not be repeatable, thus causing a problem in developing an objective diagnosis/monitoring system.
Photography has been used to aid in record keeping, but subtle changes in angle, lighting, skin tension and distance can affect the reading and therefore cause misdiagnosis. In addition, photographs, especially polaroids which are commonly used, can show color degradation over time. The newest methods of skin image tracking rely on epiluminescence microscopy (ELM). This technology looks deeper into the skin and is able to image structures up to the dermis-epidermis junction. In depth investigations have led to deduction of relevant features bearing a high correlation with malignancy. As the technique allows visualization of features not visible to the naked eye, using this technique results in higher sensitivity and specificity than that obtained with the clinical ABCD system. Typical values obtained with this method range from 92-100% for the sensitivity and 80-92% for specificity.
ELM, although better than previous techniques, has not yet been brought to the necessary level of sensitivity and specificity. There is a lack of exact correlation with structures seen in the histology. In current applications of epiluminescence microscopy technique the image capturing process involves pressing a transparent glass or plastic on the skin. This can introduce error into the system since different applications of pressure cause a different stretching of the skin which is imaged onto the camera. As there is no regulation of the pressure, the images captured are not fully repeatable. In addition, the other features by which the current ELM technology operates are extremely difficult to obtain in an automated way in a repeatable fashion. Various features which are important in the ELM are dynamic by nature and take some time before they develop. Therefore, findings may be misinterpreted due to lack of exact staging of the mole or external factors affecting the interpretation. Thus the interpretation of the features is somewhat difficult. In some systems, the lesion area is determined by manually selecting an appropriate threshold to determine the skin/lesion border. As all the parameters are then measured automatically based on this choice, the results may be biased and therefore not repeatable. Therefore, it is necessary to provide a robust system of parameters for use in diagnosis.
Other areas in which temporal comparison of skin surface images may be of use include cosmetics, skin treatment and identification. To this end a method of storing an image which is repeatable and comparable would be desirable.
Thus, it would be desirable to provide a fully automatic, sensitive, specific and cost-effective system for measurement and temporal tracking of lesion skin images which would be repeatable and comparable.